activity
20242026
collaborators

11 papers

math.PR2026

Operator level soft edge to bulk transition in -ensembles via canonical systems

Vincent Painchaud, Elliot Paquette

The stochastic Airy and sine operators, which are respectively a random Sturm-Liouville operator and a random Dirac operator, characterize the soft edge and bulk scaling limits of…

math.PR2026

Anisotropic local law for non-separable sample covariance matrices

Zhou Fan, Renyuan Ma, Elliot Paquette +1

We establish local laws for sample covariance matrices $K = N^{-1}\sum_{i=1}^N \g_i\g_i^*$ where the random vectors $\g_1, \ldots, \g_N \in \R^n$ are independent with common covari…

math.ST2025

Dyson Equation for Correlated Linearizations and Test Error of Random Features Regression

Hugo Latourelle-Vigeant, Elliot Paquette

This paper develops some theory of the Dyson equation for correlated linearizations and uses it to solve a problem on asymptotic deterministic equivalent for the test error in rand…

cs.LG2025

High-Dimensional Privacy-Utility Dynamics of Noisy Stochastic Gradient Descent on Least Squares

Shurong Lin, Eric D. Kolaczyk, Adam Smith +1

The interplay between optimization and privacy has become a central theme in privacy-preserving machine learning. Noisy stochastic gradient descent (SGD) has emerged as a cornersto…

math.PR2025

Eigenvalue distribution of the Neural Tangent Kernel in the quadratic scaling

Lucas Benigni, Elliot Paquette

We compute the asymptotic eigenvalue distribution of the neural tangent kernel of a two-layer neural network under a specific scaling of dimension. Namely, if $X\in\mathbb{R}^{n\ti…

math.PR2025

Bulk asymptotics of the Gaussian -ensemble characteristic polynomial

Gaultier Lambert, Elliot Paquette

The Gaussian -ensemble (GE) is a fundamental model in random matrix theory. In this paper, we provide a comprehensive asymptotic description of the characteristic polynomia…